Documentation of the Evaluation of CALPUFF and Other Long ...

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C.4.2.1 SUMMARY OF LRT MODEL RANKINGS FOR CTEX3 USING STATISTICAL PERFORMANCE MEASURES Table C‐5 summarizes the rankings between the six LRT models for the 11 performance statistics analyzed. Depending on the statistical metric, three different models were ranked as the best performing model for a particular statistic with CAMx being ranked first more than the other models (46%) and FLEXPART ranked first second most (36%). CALGRID was consistently ranked the worst performing model being the poorest performing model for 6 of the 11 performance statistics. In testing the efficacy of the RANK statistic for providing an overall ranking of model performance we the ranking of the six LRT models using the average rank of the 11 performance statistics versus the ranking from the RANK statistical metric (Table C‐5). The average rank of model performance for the six LRT dispersion models and the CTEX3 experiment averaged across all 11 performance statistics and the comparison to the RANK rankings was as follows: Ranking Average of 11 Statistics RANK 1. CAMx CAMx 2. SCIPUFF SCIPUFF 3. FLEXPART FLEXPART 4. HYSPLIT CALPUFF 5. CALPUFF HYSPLIT 6. CALGRID CALGRID For the CTEX3 experiment, the average rankings across the 11 statistics is nearly identical to the rankings produced by the RANK integrated statistics that combines the four statistics for correlation (PCC), bias (FB), spatial (FMS) and cumulative distribution (KS) with only HYSPLIT and CALPUFF exchanging places as the 4 th and 5 th best performing models. CALPUFF performance was weighted down in the average statistic rankings due to lower scores in the FA2 and FA5 metrics compared to HYSPLIT. If not for this, the average rank across all 11 metrics would have been the same as Draxler’s RANK score. Although this deviation did occur in the fourth and fifth ranked positions, the RANK statistic remains a valid performance statistic for indicating over all model performance of a LRT dispersion model. However, the analyst should use discretion in relying too heavily upon RANK score without consideration to which performance metrics are important measures for the particular evaluation goals. For example, if performance goals are not concerned with a model’s ability to perform well in space and time, then reliance upon spatial statistics such as the FMS in the composite RANK value may not be appropriate. In the case of this evaluation, since space/time considerations are paramount for proper LRT model performance, the RANK metric is a valuable tool to rapidly assess model performance across a broad range of metrics being evaluated. 32
Table C‐55. Summary y of model r Statisttic 1 FMSS CA FARR FLEX PODD CA TS FLEX FOEXX HYS FA22 CA FA55 CA NMSSE FLEX PCC orr R CA FB FLEX KS HYS st anking using 2 Mx S PART Mx FL PART SPLIT Mx S Mx S PART Mx S PART SPLIT nd g the statist 3 SCIPUFF CAMx LEXPART CAMx CAMx SCIPUFF SCIPUFF CAMx SCIPUFF CAMx CAMx rd tical perform 4 HYSPLIT SCIPUFF SCIPUFF SCIPUFF SCIPUFF FLEXPART FLEXPART CALPUFF CALPUFF SCIPUFF SCIPUFF th mance metri 5 CALPUFF CALPUFF HYSPLIT HYSPLIT CALPUFF HYSPLIT HYSPLIT SCIPUFF CALGRID CALPUFF CALPUFF th cs. 6 FLEXPAART CALG HYSPLIT CALG CALPUUFF CALG CALPUUFF CALG CALGRRID FLEX CALGRRID CALP CALPUUFF CALG CALGRRID HYS FLEXPAART HYS CALGRRID HYS FLEXPAART CALG th GRID GRID GRID GRID XPART PUFF GRID SPLIT SPLIT SPLIT GRID Avg. Rankinng CAMx SSCIPUFF Avg. Sccore 1. 55 2.72 RANK Rankinng CAMx SSCIPUFF RANK 1. 91 1.71 FLEXPART C.5 COMMPARISON OF O SIX LRT MMODEL MODDELING PERFFORMANCE USING THE CCAPTEX‐5 EXPERIMMENT C.5.1 SPATIAL ANAL LYSIS OF MOODEL PERFORMANCE Figure C‐ ‐30 displays the FMS spaatial analysiss performancce metrics foor the six LRT models annd the CTEXX5 tracer study field expeeriment. SCCIPUFF (22.677%) and CAMMx (22.66%) ) models aree the two best performing g models for the FMS staatistic with nnearly identiccal scores. TThey are followed by HYSPLIT (18.5%), CAALPUFF (17.55%), FLEXPARRT (17.2), annd CALGRID (16.1%). Figure C‐ ‐30. Figure of o Merit in SSpace (FMS) ) statistical pperformancee metric for the six LRT models aand CAPTEX Release 5. 3.0 FLEXPART 1.44 33 HYSPLIT 4.0 CALPUFF 1.43 CALPUUFF CALGGRID 4.277 5. 55 HYSPLIT CALGGRID 1.255 0. 98
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Documentation of the Evaluation of
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FOREWARD This report documents the
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2.4.3 ATMES‐II Model Evaluation A
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EXECUTIVE SUMMARY ABSTRACT The CALP
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OVERVIEW OF APPROACH Up to six LRT
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CALPUFF performance is evaluated by
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Table ES‐2. ATMES‐II spatial an
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• CALPUFF tended to overstate the
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• The best performing CALPUFF con
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2009a). The key findings from the C
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1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2
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2.4 2 1.6 1.2 0.8 0.4 0 EXP4A EXP4B
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Figure ESS‐4. RANK statistical pe
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Evaluatioon of Six LRT T Dispersion
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Table ES‐6. Summary of model rank
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eproduce the northwest to southeast
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ETEX LRT Dispersion Model Sensitivi
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CONCLUSIONS OF LRT DISPERSION MODEL
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The CAMx and CALGRID Eulerian photo
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July 1980. Both experiments examine
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1.3 ORGANIZATION OF REPORT Chapter
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puffs expand until they exceed the
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that performance evaluation be base
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The ETEX real‐time LRT modeling p
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The ETEX study has formulated the f
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In this study we expand the LRT mod
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AM ∩ AP FMS = × 100% (2‐2) A
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Factor of α (FAα): FAα represent
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3.0 1980 GREAT PLAINS FIELD STUDY 3
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compact discs, which were used to o
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ILEVZI = 1 Layer of winds to use in
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MCHEM = 0 No chemical transformatio
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Table 3‐6. CALPUFF/CALMET experim
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Table 3‐11. CALPUFF/MMIF sensitiv
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evaluation studies and evaluate whe
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Tables 3‐13 and Figures 3‐2 thr
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140% 120% 100% 80% 60% 40% 20% 0%
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30% 20% 10% 0% ‐10% ‐20% ‐30%
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120% 100% 80% 60% 40% 20% 0% ‐20%
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20% 10% 0% ‐10% ‐20% ‐30% ‐
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The fitted Gaussian plume statistic
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0% ‐10% ‐20% ‐30% ‐40% ‐5
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300% 250% 200% 150% 100% 50% 0% 300
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60% 40% 20% 0% ‐20% ‐40% ‐60%
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with APS, implementing the slug opt
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the amount of time that the tracer
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Figure 4‐1. CALPUFF/CALMET UTM mo
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compact discs, which were used to o
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Table 4‐4. CALPUFF parameters use
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Table 4‐8. CALPUFF/MMIF sensitivi
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the fitted Gaussian plume is not a
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Figure 4‐2. Comparison of predict
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Figure 5‐1. Location of Dayton an
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MM5 runs, the first without FDDA (i
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Table 5‐3. MM5 sensitivity tests
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Table 5‐6. Definition of the CALM
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performance at the monitor location
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35% 30% 25% 20% 15% 10% 5% 0% 35% 3
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40% 35% 30% 25% 20% 15% 10% 5% 0% F
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40% 35% 30% 25% 20% 15% 10% 5% 0% E
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5.4.1.4 Comparison of CALPUFF CTEX3
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0.48 0.36 0.24 0.12 0 ‐0.12 16% 1
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CTEX3 discussed in Section 5.4.1. A
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CALPUFF sensitivity simulations are
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14. Across all the spatial statisti
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sensitivity tests. The “B” seri
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‐0.1 ‐0.2 0 0.8 0.7 0.6 0.5 0.4
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6.0 1994 EUROPEAN TRACER EXPERIMENT
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Figure 6‐2a. Surface synoptic met
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Figure 6‐3a. Distribution of the
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36 kilometers and the vertical stru
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splitting flag near sunset (hour 17
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experienced during the original ETE
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2 1 0 ‐1 ‐2 3 2 1 0 23‐Oct 23
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70% 60% 50% 40% 30% 20% 10% 0% Figu
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Figure 6‐9. Factor of Exceedance
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eceiving a 0.0 score. Figure 6‐13
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Table 6‐1. Summary of model ranki
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plume spread and observed surface c
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Figure 6‐16c. Comparison of spati
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• NoPiG: The tracer emissions wer
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Using the NMSE statistical performa
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6.4.3.2 Effect of PiG on Model Perf
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80 70 60 50 40 30 20 10 0 1 2 3 4 5
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Table 6‐3. Summary of CALPUFF puf
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0.2 0.18 0.16 0.14 0.12 0.1 0.08 0.
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Figure 6‐ ‐22 displays the t sp
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Figure 6‐ ‐23a. Global model pe
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Figure 6‐24. Figure of Merit (FMS
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7.0 REFERENCES Anderson, B. 2008. T
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EPA, 1984: Interim Procedures for E
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Mlawer, E.J., S.J. Taubman, P.D. Br
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Page 187 and 188: Table A‐1. Wind speed and wind di
Page 189 and 190: Table A‐3. Definition of the CTEX
Page 191 and 192: Figure A‐ ‐1. Wind speed bias (
Page 193 and 194: Figure A‐ ‐3. Humidity bias and
Page 195 and 196: Table A‐5. Comparison of CTEX5 MM
Page 197 and 198: B.1 CALMET MODEL EVALUATION TO IDEN
Page 199 and 200: Figure B‐ ‐1 displays th he win
Page 201 and 202: Table B‐2a. Summary wind speed mo
Page 203 and 204: B.2 CONCLUSIONS OF CTEX3 CALMET SEN
Page 205 and 206: C.1 INTRODUCTION In this section, t
Page 207 and 208: C.2.2 HYYSPLIT GLOB BAL STATISTIICS
Page 209 and 210: The final panel in Figure C‐3 (bo
Page 211 and 212: Figure C‐ ‐5. Global model m pe
Page 213 and 214: C.3 CAMX SENSITIVITY TESTS Followin
Page 215 and 216: ACM2 Kzz combinatio ons rank as the
Page 217 and 218: Figure C‐ ‐10. Spatial model pe
Page 219 and 220: Figure C‐ ‐12. Global model per
Page 221 and 222: Figure C‐ ‐13. Spatial model pe
Page 227 and 228: Table C‐3. CAMx FMS and POD spati
Page 229 and 230: Figure C‐ ‐20. False Alarm Rate
Page 231 and 232: Figure C‐ ‐23. Factor of o Exce
Page 233 and 234: The PCC values for th he six LRT mo
Page 235: The RANK statistical performancce m
Page 239 and 240: Results foor the TS me etric are pr
Page 241 and 242: Figure C‐ ‐35. Factor of o 2 (F
Page 243 and 244: a negativve FB. The best b performm
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Page 247: United States Environmental Protect
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